Overview
Data Profiling is a crucial first step in data management and analytics. It involves using analytical techniques to discover the true state of data, including its patterns, distributions, and anomalies. By profiling data, organizations can identify quality issues early and determine if the data is fit for its intended purpose.
Key Activities
- Structure Discovery: Validating that data is consistent and formatted correctly.
- Content Discovery: Looking into individual data records to find errors (e.g., null values, outliers).
- Relationship Discovery: Identifying how data elements overlap or relate across different tables or datasets.
Benefits
- Improved data quality and reliability.
- Faster data integration and migration projects.
- Better understanding of source systems.